Intracellular autofluorescence: a biomarker for epithelial cancer stem cells

Abstract

Cancer stem cells (CSCs) are thought to drive tumor growth, metastasis and chemoresistance. Although surface markers such as CD133 and CD44 have been successfully used to isolate CSCs, their expression is not exclusively linked to the CSC phenotype and is prone to environmental alteration. We identified cells with an autofluorescent subcellular compartment that exclusively showed CSC features across different human tumor types. Primary tumor–derived autofluorescent cells did not overlap with side-population (SP) cells, were enriched in sphere culture and during chemotherapy, strongly expressed pluripotency-associated genes, were highly metastatic and showed long-term in vivo tumorigenicity, even at the single-cell level. Autofluorescence was due to riboflavin accumulation in membrane-bounded cytoplasmic structures bearing ATP-dependent ABCG2 transporters. In summary, we identified and characterized an intrinsic autofluorescent phenotype in CSCs of diverse epithelial cancers and used this marker to isolate and characterize these cells.

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Figure 1: Identification of autofluorescent cancer stem cells.
Figure 2: In vitro and in vivo characterization of autofluorescent cells.
Figure 3: Invasiveness of autofluorescent cells.
Figure 4: Autofluorescent cells are resistant to chemotherapy.
Figure 5: Mechanism of autofluorescence in cancer stem cells.
Figure 6: Source of autofluorescence in cancer stem cells.

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Acknowledgements

We thank A. González-Neira and L. Moreno from the CNIO Human Genotyping-CEGEN Unit for performing the TaqMan OpenArray SNAP analysis, and S.M. Trabulo and M. Tatari for their excellent in vivo technical assistance. The research was supported by the ERC Advanced Investigator Grant (Pa-CSC 233460), the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 256974 (EPC-TM-NET) and no. 602783 (CAM-PaC), the Associazione Italiana Ricerca Cancro (AIRC grant no. 12182 to A.S.), the Italian Cancer Genome Project Ministry of University and Research (FIRB RBAP10AHJB to A.S.), the FIMP-Italian Ministry of Health (CUP_J33G13000210001), the Subdirección General de Evaluación y Fomento de la Investigación, Fondo de Investigación Sanitaria (PS09/02129 & PI12/02643) and the Programa Nacional de Internacionalización de la I+D, Subprogramma: FCCI 2009 (PLE2009-0105; both Ministerio de Economía y Competitividad (es), Spain). M.C. was supported by the La Caixa Predoctoral Fellowship Program.

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Contributions

I.M.-L. acquired, analyzed and interpreted data as well as developed the study concept and drafted the manuscript; J.D. and A.B. performed the in vivo experiments; E.L., S.A., M.C., A.G.S. and S.Z. acquired and analyzed in vitro data; J.C.-T. designed the microchip-based single-cell assay; D.M. characterized the autofluorescence signal by confocal microscopy and developed the protocol for automated analysis of autofluorescence; M.H., M.E., J.K. and A.S. provided extensively characterized PDAC samples; B.S. and C.H. developed the study concept, obtained funding, interpreted the data and wrote the manuscript.

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Correspondence to Bruno Sainz Jr or Christopher Heeschen.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Screening for cancer stem cell marker(s)

(a) Flow cytometry analysis of CD133 at increasing times to analysis. Cells were trypsinized, stained, transferred to RPMI medium and then flow cytometry analysis was performed with 0, 10, 20, or 60 min delay. (b) Flow cytometry analysis of CD44+CD133+ and CD44+cMet+ in 185 (left panel) and 215 cells cultured as adherent cells or spheres. (c) Representative in vivo tumorigenicity of cells sorted for different surface marker (combinations). * For statistical analysis, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/). LDA is based on the Poisson single-hit model, which assumes that the number of biological active cells in each group varies according to a Poisson distribution, and a single biologically active cell is sufficient for inducing tumor formation. n.s., not significant.

Supplementary Figure 2 Screening for cancer stem cell marker(s)

(a) Representative cytometry plots for side population (SP) and non-side population (Non-SP) cells derived from primary PDAC tissue (untreated or treated with FTC) (left panel). Representative images of sphere formation for SP versus non-SP cells and subsequent quantification (right panel). (b) In vivo tumorigenicity of SP versus non-SP cells (top row, left panel), of aldehyde dehydrogenases (ALDH) negative versus ALDH positive (top row, right panel), adherent versus sphere-derived cells (bottom row, left panel), and Fluo versus Fluo+ cells (bottom row, right panel). * For statistical analysis, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/). n.s., not significant.

Supplementary Figure 3 Screening for cancer stem cell marker(s)

In vivo tumorigenicity of primary cells sorted for various CSC markers. * For statistical analysis, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/). n.s., not significant.

Supplementary Figure 4 Identification of autofluorescent cancer stem cells

(a) Representative cytometry plots showing no excitation of autofluorescence with 561 nm yellow-green laser (left panel) and with 640 nm red laser (right panel) using the indicated filters. (b) Emission spectra for GFP and autofluorescence, respectively. (c) RTqPCR analysis of GFP mRNA expression. Control values for each sample were compared to a standard curve comprised of serially diluted GFP DNA (left panel). Western blot analysis of GFP protein expression in indicated samples (right panel). (d) Flow cytometry of cell size for Fluo+ and Fluo cells, respectively.

Supplementary Figure 5 Identification of autofluorescent cancer stem cells

(a) Genotyping comparison for unsorted, sorted Fluo+ and sorted Fluo from 3 different PDX samples. Sample groups shared a 100% similar genotype profile (upper table). Graph sample for the SNP rs11199914 showing the same genotype profile between each patient tumor sample (lower panel). (b) Flow cytometry analysis of autofluorescent content in a freshly digested patient sample (left panel), gated for EPCAM+ cells in Fluo+ population (upper right) and Fluo- (lower panel). (c) Flow cytometry analysis of stroma and epithelial cells in a freshly digested patient tumor stained for EpCAM. EpCAM- cells (stroma) were gated to analyze the autofluorescent content.

Supplementary Figure 6 Identification of autofluorescent cancer stem cells

(a) Representative flow cytometry plots illustrating the gating strategy used for autofluorescence analyses. (b) Representative flow cytometry plots for AnnexinV staining in Fluo+ and Fluo cells.

Supplementary Figure 7 Characterization of autofluorescent cancer stem cells

(a) Flow cytometry analysis of autofluorescence content in CRC-014 and CRC-010 tumors (left panel). RT-qPCR analysis of pluripotency-associated gene expression in sorted Fluo+ and Fluo cells from CRC-014 and CRC-010 (n=2, performed in triplicate). Data are normalized for ß-actin expression (right panel). (b) Flow cytometry analysis of autofluorescence content in HCC-6 cells (left panel), RT-qPCR analysis of pluripotency-associated gene expression in primary HCC sorted for Fluo+ and Fluo cells. Data are normalized for ß-actin expression and performed in triplicate (right panel). (c) Flow cytometry analysis of autofluorescence content in Lung-005 tumors (left panel). RT-qPCR analysis of pluripotency-associated gene expression in sorted NSCLC Fluo+ and Fluo cells. Data are normalized for ß-actin expression and performed in triplicate (right panel). (d) Autofluorescent content in different primary patient and PDX tumors. Statistical significance was assessed by Mann-Whitney test.

Supplementary Figure 8 Characterization of autofluorescent cancer stem cells

(a) Polydimethyl-siloxane post-arrays containing several thousand nano-volume wells (left panel). Representative images of single Fluo+ cells giving rise to either (i) two Fluo+ cells or (ii) one Fluo and one Fluo+ cell. Arrows indicate Fluo+ cells (upper right panels). Representative images of a Fluo cells giving rise to two Fluo cells (lower right panel). (b) In vivo serial passaging of Fluo and Fluo+ cells derived from respective tumors originally generated from 103 cells. (c) Flow cytometry plot for autofluorescent content in PDAC PDX single cell-derived tumor (left panel). RT-qPCR analysis of pluripotency-associated gene expression in sorted Fluo+ and Fluo cells obtained from PDAC PDX single cell-derived tumor (right panel). Data are normalized for ß-actin expression and performed in triplicate. Error bars (c) s.d. Statistical significance was assessed by Mann-Whitney test. For statistical analysis, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/).

Supplementary Figure 9 Characterization of autofluorescent cancer stem cells

(a) RT-qPCR analysis of pluripotency-associated gene expression in sorted Fluo and Fluo+ cells derived from PDAC-Tumor-02, freshly digested and without culture or supplementation with Riboflavin. Data are normalized using ß-actin expression and performed in triplicate. (b) In vivo tumorigenicity of serially diluted sorted Fluo and Fluo+ cells derived from freshly resected PDX tumors and primary tumors, respectively, without any culturing or supplementation with Riboflavin (right panel). (c) Unsorted cells were treated with Gemcitabine for 12 days. Following treatment, cells were sorted for autofluorescence and injected into mice. Shown are the tumorigenicity results of long-term Gemcitabine treated Fluo and Fluo+ sorted cells after two months. Error bars (a) s.d. Statistical significance was assessed by Mann-Whitney test. For statistical analysis of tumorigenicity, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/).

Supplementary Figure 10 Origin and mechanism of autofluorescence

(a) Intracellular ATP content in sorted Fluo+ and Fluo cells and unsorted cells. (b) RT-qPCR analysis of ATG12 gene expression in sorted Fluo+ and Fluo cells of different primary PDAC PDX in vitro cultures (n = 2, each performed in duplicate) (upper panel). Western blot analysis of LC3 protein expression in sorted Fluo+ and Fluo primary PDAC PDX in vitro cells (lower panel). (c) Representative flow cytometry analysis for autofluorescence content using specific autophagy inhibitors (E64D [10 μM] plus Pepstatin-A [1 μg/ml]) or the autophagy inducer Rapamycin (100 ng/ml). (d) Representative flow cytometry plots illustrating the recovery of autofluorescence following the addition of various vitamins. Error bars (a) s.d. of two technical replicates.

Supplementary Figure 11 Source of autofluorescence in cancer stem cells

(a) RT-qPCR analysis of pluripotency-associated gene expression in sorted Fluo and Fluo+ PDAC PDX in vitro cultured (185) cells either untreated or pretreated with 30 μM riboflavin for 24 h. Data are normalized for β-actin expression (left panel). Tumorigenicity of serially diluted sorted Fluo+ and Fluo 185 cells pre-treated with riboflavin 30 μM (right panel). (b) Panc01 and implanted subcutaneously (upper panel) and orthotopically (lower panel), and treated with or without riboflavin prior to analysis. Error bars (a) s.d. of two technical replicates. For statistical analysis of tumorigenicity, we used limiting dilution analysis (LDA; http://bioinf.wehi.edu.au/software/elda/).

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Miranda-Lorenzo, I., Dorado, J., Lonardo, E. et al. Intracellular autofluorescence: a biomarker for epithelial cancer stem cells. Nat Methods 11, 1161–1169 (2014). https://doi.org/10.1038/nmeth.3112

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